Shohei Enomoto

According to our database, Shohei Enomoto authored at least 10 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Test-time Adaptation Meets Image Enhancement: Improving Accuracy via Uncertainty-aware Logit Switching.

Shohei Enomoto, Naoya Hasegawa, Kazuki Adachi, Taku Sasaki, Shin'ya Yamaguchi, Satoshi Suzuki, Takeharu Eda

CoRR, 2024

Test-time Similarity Modification for Person Re-identification toward Temporal Distribution Shift.

Kazuki Adachi, Shohei Enomoto, Taku Sasaki, Shin'ya Yamaguchi

CoRR, 2024

Improving Image Coding for Machines through Optimizing Encoder via Auxiliary Loss.

Kei Iino, Shunsuke Akamatsu, Hiroshi Watanabe, Shohei Enomoto, Akira Sakamoto, Takeharu Eda

CoRR, 2024

2023

Incorporating Supervised Domain Generalization into Data Augmentation.

Shohei Enomoto, Monikka Roslianna Busto, Takeharu Eda

CoRR, 2023

A Video Object Detection Method of ECNet Based on Frame Difference and Grid Cell Confidence.

Shunsuke Akamatsu, Kei Iino, Hiroshi Watanabe, Shohei Enomoto, Xu Shi, Akira Sakamoto, Takeharu Eda

Proceedings of the 12th IEEE Global Conference on Consumer Electronics, 2023

2022

AugNet: Dynamic Test-Time Augmentation via Differentiable Functions.

Shohei Enomoto, Monikka Roslianna Busto, Takeharu Eda

CoRR, 2022

Inter-Feature-Map Differential Coding of Surveillance Video.

Kei Iino, Miho Takahashi, Hiroshi Watanabe, Ichiro Morinaga, Shohei Enomoto, Xu Shi, Akira Sakamoto, Takeharu Eda

Proceedings of the 11th IEEE Global Conference on Consumer Electronics, 2022

2021

Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems.

Shohei Enomoto, Takeharu Eda

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

ECNet: A Fast, Accurate, and Lightweight Edge-Cloud Network System based on Cascading Structure.

Libo Hu, Tao Wang, Hiroshi Watanabe, Shohei Enomoto, Shi Xu, Akira Sakamoto, Takeharu Eda

Proceedings of the 9th IEEE Global Conference on Consumer Electronics, 2020

2019

An Expandable Deep Learning Inference Framework With Adjustability to Workload Requirement.

Takeharu Eda, Sanae Muramatsu, Shohei Enomoto, Shi Xu

Proceedings of the 2019 IEEE International Conference on Image Processing, 2019